Max Savery joined the group in 2022. His research focuses on efficient spatio-temporal data collection. Particular attention goes to the development of (Bayesian) optimal designs that integrate multiple types of data sources, for the purpose of more efficiently surveying difficult-to-collect spatio-temporal data. Furthermore, Max supports the master course in experimental design taught at the faculty of bioscience engineering. In his non-statistical life he likes to ride bikes and paint.
Experience
During his bachelor’s degree Max focused on genetics, and was subsequently awarded research fellowship positions in genomics and medical informatics at the National Institutes of Health (United States, 2017-2020).
Education
MSc in Statistics and Data Science
distinction, KU Leuven (2022)
Publications
[4] Savery, M. and Luca, S. (2025). Bayesian Optimal Design using integrated presence-only and presence-absence data for occupancy modelling. Bayesian Analysis. Under review.
[3] Savery, M. and Luca, S. (2024). Bayesian optimal design for species distribution modelling. Presented at the Flanders AI Research day 2024, Ghent, Belgium. Conference presentation. Oct. 2024.
PDF
[2] Savery, M., Rogers, W. J., Pillai, M., Mork, J. G., and Demner-Fushman, D. (2020). Chemical Entity Recognition for MEDLINE Indexing.. AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science. 2020, 561-568.
[1] Savery, M., Ben Abacha, A., Gayen, S., and Demner-Fushman, D. (2020). Question-driven summarization of answers to consumer health questions. Scientific Data. 7.